Project description:The main aim of this paper is to give an improvement of the recent result on the sharpness of the Jensen inequality. The results given here are obtained using different Green functions and considering the case of the real Stieltjes measure, not necessarily positive. Finally, some applications involving various types of f-divergences and Zipf–Mandelbrot law are presented.

| S-EPMC6290690 | biostudies-other

Identifying Critical States of Complex Diseases by Single-Sample Jensen-Shannon Divergence.

Project description:MotivationThe evolution of complex diseases can be modeled as a time-dependent nonlinear dynamic system, and its progression can be divided into three states, i.e., the normal state, the pre-disease state and the disease state. The sudden deterioration of the disease can be regarded as the state transition of the dynamic system at the critical state or pre-disease state. How to detect the critical state of an individual before the disease state based on single-sample data has attracted many researchers' attention.MethodsIn this study, we proposed a novel approach, i.e., single-sample-based Jensen-Shannon Divergence (sJSD) method to detect the early-warning signals of complex diseases before critical transitions based on individual single-sample data. The method aims to construct score index based on sJSD, namely, inconsistency index (ICI).ResultsThis method is applied to five real datasets, including prostate cancer, bladder urothelial carcinoma, influenza virus infection, cervical squamous cell carcinoma and endocervical adenocarcinoma and pancreatic adenocarcinoma. The critical states of 5 datasets with their corresponding sJSD signal biomarkers are successfully identified to diagnose and predict each individual sample, and some "dark genes" that without differential expressions but are sensitive to ICI score were revealed. This method is a data-driven and model-free method, which can be applied to not only disease prediction on individuals but also targeted drug design of each disease. At the same time, the identification of sJSD signal biomarkers is also of great significance for studying the molecular mechanism of disease progression from a dynamic perspective.

| S-EPMC8212786 | biostudies-literature

The genome sequence of the high brown fritillary, <i>Fabriciana adippe</i> (Dennis & Schiffermuller, 1775).

Project description:We present a genome assembly from an individual female Fabriciana adippe (the high brown fritillary; Arthropoda; Insecta; Lepidoptera; Nymphalidae). The genome sequence is 485 megabases in span. Most of the assembly (99.98%) is scaffolded into 29 chromosomal pseudomolecules with the Z sex chromosome assembled. The complete mitochondrial genome was also assembled and is 15.1 kilobases in length. Gene annotation of this assembly in Ensembl identified 13,536 protein coding genes.

| S-EPMC10186063 | biostudies-literature

Differences Between APOE Carriers and Non-APOE Carriers on Neurocognitive Tests: Jensen Effects?

Project description:BackgroundBeing a carrier of the apolipoprotein E (APOE) ε4 allele is a clear risk factor for development of Alzheimer's disease (AD). On some neurocognitive tests, there are smaller differences between carriers and noncarriers, while other tests show larger differences.AimsWe explore whether the size of the difference between carriers and noncarriers is a function of how well the tests measure general intelligence, so whether there are Jensen effects.MethodsWe used the method of correlated vectors on 441 Korean older adults at risk for AD and 44 with AD.ResultsCorrelations between APOE carriership and test scores ranged from -.05 to .11 (normal), and -.23 to .54 (AD). The differences between carriers and noncarriers were Jensen effects: r = .31 and r = .54, respectively.ConclusionA composite neurocognitive score may show a clearer contrast between APOE carriers and noncarriers than a large number of scores of single neurocognitive tests.

| S-EPMC10852421 | biostudies-literature

MD-P001

Project description:Comprehensive ecosystem-specific 16S rRNA gene databases with automated taxonomy assignment (AutoTax) provide species-level resolution in microbial ecology

| PRJEB26558 | ENA

Cotton Fiber Cells: Germplasm Line MD 52ne vs. Germplasm Line MD 90ne

Project description:Transcriptional profiling of cotton fiber cells from two cotton germplasm lines, MD 52ne and MD 90ne. Comparison of fiber cell transcription profiles is between the two germplasm lines and over a developmental time-course from 8 to 24 days post anthesis in four day intervals.

2009-01-14 | GSE14388 | GEO

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